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Unit information: Computational Neuroscience in 2018/19

Please note: It is possible that the information shown for future academic years may change due to developments in the relevant academic field. Optional unit availability varies depending on both staffing and student choice.

Unit name Computational Neuroscience
Unit code COMS30127
Credit points 10
Level of study H/6
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Dr. Houghton
Open unit status Not open




School/department Department of Computer Science
Faculty Faculty of Engineering


This unit has two versions, COMS30127 for undergraduate students, and COMSM2127 for postgraduate students.

Aims are to provide the student with an understanding of computational principles of biological computations performed in the brain by: single neurons, network of neurons, and interacting brain areas.

Intended learning outcomes

After successful completion of this unit, the student will

  • Be inspired by the computational principles of the brain in their future engineering work.
  • Be prepared to do research on the brain with understanding of brain s purpose (i.e., information processing).
  • For each levels of abstraction (single neuron, network of neurons, interacting brain areas): understand the assumptions made by the models, validity of the assumptions, and computational principles.
  • Be able to simulate simple models of neurons, networks, and cortical areas in Matlab or Python.

Teaching details

20 hours of lectures, 10 hours of laboratory sessions

Assessment Details

Coursework (20%), exam (80%)

All students need to do two courseworks in Matlab or Python which address the fourth learning outcome (Be able to simulate simple models of neurons, networks, and cortical areas in Matlab or Python).

Reading and References

Lecture notes. Background reading to include: Peter Dayan, Larry F Abbott Theoretical Neuroscience MIT-Press, 2001 ISBN: 0-262-04199-5 Price: £31.57 Recommended